Security Information and Event Management, popularly known as SIEM, is a frankenword of security information management (SIM) and security event management (SEM) devised in 2005 by Gartner’s Amrit Williams and Mark Nicolett. SIEM is defined as a particular type of technology that enables the detection of threats and responds to security incidents by conducting real-time gathering and analyses of historical security occasions from a wide range of data sources. Essentially, the technology was invented to handle vast chunks of alerts emanating from intrusion prevention systems (IPS) and intrusion detection systems (IDS) that used to overwhelm IT departments. SIEM allowed the aggregation of events and excellent analyses of events inside networks while assisting the organization in improving threat detection. During that time, SIEM was referred to as Legacy SIEMs. They mainly focused on gathering and correlating security incidents from numerous sources such as firewalls and anti-malware systems, IDSs, endpoint security, and network infrastructures like WAPs and servers. A tremendous number of businesses adopted SIEM to boost their cybersecurity posture, but with time, issues with this technology became apparent:
- SIEM suffered from limited effectiveness: where the available data was inflexible, the technology couldn’t process it.
- Maintenance and operation difficulty: this introduced complexity and drained organization resources.
- Generation of huge chunks of false positives: this created an additional workload for the security department.
- The technology struggled to keep pace with evolving threats: businesses were at risk of potential cyber-attacks resulting in huge losses.
Tactically, cyber threats are polymorphic more than static; they can constantly change their tactics to escape detection. As such, threat detection technologies should process tremendous amounts of data and be vast enough to recognize new patterns with the data. Following the limitations and inefficiencies of convectional SIEMs systems, industry commentators started predicting their demise. Nevertheless, that didn’t happen – SIEM has retained its position as an essential technology adopted by enterprises. Instead, SIEM evolved into a better way of detecting threats. While SIEM once depended on few data sources, the evolved version of SIEM, the Next-generation SIEM systems, can process vast volumes of data and correlate in a real-time fashion. Also referred to as Analytics-Driven SIEMs, SIEM 3.0, Next-Generation SIEMs, or Next-Gen SIEM, the new technology boasts modern features that offer splendid security capabilities to enterprises and security pundits. Next-Gen SIEM:
- Allows fast integration with an organizations’ infrastructure through open architecture to embrace both the cloud and on-premise resources;
- Adopts real-time visualization resources to comprehend the most essential and high-risk activities;
- Apply scenario and behavioral analytics to highlight and detect any behavior changes;
- Apply threat intelligence from tailored, commercial, and open-source sources;
- Offer a resilient framework to allow efficient workflow implementation; and
- Enables the measurement of states against regulatory authorities to allow efficient risk prioritization and management.
So, what’s the difference between the traditional SIEM and Next-Generation SIEM? Simply, the Next-Gen SIEM is an improved version of traditional SIEM, implying that the former offers a more secure threat detection and mitigation system than the latter. Standard or traditional SIEM technologies focus on gathering and indexing log outputs from a handful of devices and/or applications. Basically, SIEM solutions are applied in searching and detecting specific log details. For instance, conducting device searches and displaying all logs for a specific day. Usually, it generates tens to hundreds of data pages, more (thousands of pages) where the device/application is faulty. Therefore, traditional SIEM offers parameters that allow refined searches at precise timing or specific log event outputs. And again, the process requires a high degree of expertise by the end-user.
In contrast, Next-Gen SIEM solutions ingest log and flow information – apply threat models to identify threats without human input. Next-Gen SIEM solutions leverage complex models (algorithms) to detect and match threat patterns to specific threat types like DDoS attacks, malware infections, insider attacks, and loss of private data. They apply machine learning algorithms to recognize anomalies in devices and applications and correlate such events with different triggers that can be matched with threat models. The techniques comprise behavior-enabled security analytics that applies a set of statistical, supervised, and unsupervised algorithms custom-built for cybersecurity to identify known and unknown threats. Upon finding the match, an alert is issued, which unfolds the kind of threat, the device, the user, and the type of mitigation to be executed. Next-Gen SIEM solutions are architecture to recognize cyber threats in seconds of becoming “lethal.” They are designed to prevent brute force attacks, corruption of credentials, as well as insider threats. These capabilities are absent in traditional SIEMs.
Next-Gen SIEM solutions are developed on a big data platform to handle tremendous amounts of data generated by organizations effectively. This enables efficient and real-time consumption and analyses of hundreds if not thousands of terabytes of data while supporting sustainable long-term information retention. Also, SIEM 3.0 offers users data portability; it allows data storage via an open data model. That way, users are allowed to keep one copy of their security data, and that information would be availed in other applications when required. Moreover, Next Generation SIEM solutions are deployable on ordinary hardware platforms and enable the improvement of safety in those platforms.
Next-Gen SIEM solution upgrades the collected information by supplementing extra contextual data such as user information, details about the assets, IP address, vulnerability, and threat intelligence. Upon triggering an alert, contextual information is leveraged to comprehend the severity depending on the user; assets applied, and the kind of information at risk.
In conclusion, traditional SIEM solutions were built when the IT industry focused only on safeguarding their perimeter. Over time, these solutions struggled to meet the overwhelming security challenges in the IT environment calling for the advancement of the technology to Next-Generation SIEM. The next generation of SIEM supports improved security visibility, response, and posture and minimizes analytical and administration burdens.